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- Tasks: Create innovative models for physical AI agents and solve complex human challenges.
- Company: Join Google DeepMind's diverse team at the forefront of AI and robotics.
- Benefits: Competitive salary, inclusive culture, and opportunities for impactful research.
- Why this job: Make a real difference in robotics and AI while working with cutting-edge technology.
- Qualifications: PhD or significant research experience in relevant quantitative fields.
- Other info: Collaborative environment with a focus on ethical AI and safety.
The predicted salary is between 36000 - 60000 £ per year.
London, UK
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Our Mission
At Google DeepMind, we believe AI is a pivotal tool for scientific advancement. Our interdisciplinary team of experts works at the cutting edge of machine learning to create technology that benefits the public. Safety and ethical considerations are foundational to every project we undertake.
About Us
Our Robotics Team is seeking Research Scientists to push the boundaries of embodied AI. We aim to build intelligent systems capable of meaningful interaction with the physical world to solve complex human challenges. We value the synergy between theoretical algorithmic research and large-scale practical deployment.
The Role
In this role, you will spearhead the creation of innovative models and algorithms for physical AI agents. We need inventive problem solvers with high-level programming skills to design agents that are deeply integrated with the real world. You will collaborate to evolve foundation models, test prototypes, and apply findings to actual robotics hardware. Expertise in reinforcement learning, multimodal models, and large-scale training is highly desirable.
- Architect and train advanced models to expand the functional limits of robotic systems.
- Develop high-quality code to prototype and refine research concepts rapidly.
- Contribute effectively within dynamic, cross-functional teams to achieve high-impact goals.
- Apply specialized knowledge in core robotics domains, including:
- Sim-to-real transfer and reinforcement learning techniques
- Imitation learning
- VLA models and generative architectures
- Reactive fast-feedback low level controllers
About You
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- A PhD in a relevant quantitative field or significant professional research experience.
- Deep theoretical understanding of algorithmic frameworks like:
- Advanced reinforcement and imitation learning methodologies.
- Multimodal generative modeling and efficient inference systems.
- Scaling large-scale vision-language or video foundation models.
Applications close on Monday 23rd March at 5pm GMT.
Research Scientist, Multisensor Robotics & Dexterity employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, Multisensor Robotics & Dexterity
✨Tip Number 1
Network like a pro! Reach out to people in the robotics and AI fields on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to reinforcement learning and robotics. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms – it’s key to impressing both technical and non-technical interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Research Scientist, Multisensor Robotics & Dexterity
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for robotics and AI shine through! We want to see how your experiences and interests align with our mission at Google DeepMind. Make it personal and engaging!
Tailor Your CV: Don’t just send a generic CV! Highlight your relevant skills and experiences that match the job description. We’re looking for specific examples of your work in reinforcement learning and multimodal models, so make sure to showcase those!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the role. Be clear about your motivations and how your background can contribute to our Robotics Team. Keep it concise but impactful!
Apply Through Our Website: Make sure to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for the position. Plus, it’s super easy to do!
How to prepare for a job interview at Google DeepMind
✨Know Your Stuff
Make sure you have a solid grasp of the key concepts related to reinforcement learning, multimodal models, and generative architectures. Brush up on your theoretical knowledge and be ready to discuss how these frameworks can be applied in real-world scenarios.
✨Showcase Your Projects
Prepare to talk about your previous research or projects that align with the role. Highlight any innovative models or algorithms you've developed, especially those that demonstrate your ability to solve complex problems in robotics.
✨Collaborative Spirit
Since the role involves working within dynamic, cross-functional teams, be ready to share examples of how you've successfully collaborated with others. Emphasise your communication skills and how you can convey technical results to both experts and non-experts.
✨Real-World Applications
Think about how your academic research can translate into practical applications. Be prepared to discuss challenges you've faced with hardware integration and how you approached solving them, as this will show your readiness to tackle real-world problems.